Optimization–Simulation Model for Planning Supply Transport to Large Infrastructure Public Works Located in Congested Urban Areas

This article proposes an optimization–simulation model for planning the transport of supplies to large public infrastructure works located in congested urban areas. The purpose is to minimize their impact on the environment and on private transportation users on the local road network. To achieve this goal, the authors propose and solve an optimization problem for minimizing the total system cost made up of operating costs for various alternatives for taking supplies to the worksite and the costs supported by private vehicle users as a result of increased congestion due to the movement of heavy goods vehicles transporting material to the worksite. The proposed optimization problem is a bi-level Math Program model. The upper level defines the total cost of the system, which is minimized taking into account environmental constraints on atmospheric and noise pollution. The lower level defines the optimization problem representing the private transportation user behavior, assuming they choose the route that minimizes their total individual journey costs. Given the special characteristics of the problem, a heuristic algorithm is proposed for finding optimum solutions. Both the model developed and the specific solution algorithm are applied to the real case of building a new port at Laredo (Northern Spain). A series of interesting conclusions are obtained from the corresponding sensitivity analysis.     

Providing effective feedback, monitoring and evaluation to on-line collaborative learning discussions

Learning and knowledge building have become critical competences for people in the knowledge society era. In this paper, we propose a sociolinguistic dialogue model for understanding how learning evolves and how cognitive process is constructed in on-line discussions. The knowledge extracted from this model is used to assess participation behavior, knowledge building and performance. The ultimate purpose is to provide effective feedback, evaluation and monitoring to the discussion process. Seven hundred students from the Open University of Catalonia in Spain participated in this study. Results showed that learning and knowledge building may be greatly enhanced by presenting selected knowledge to learners as for their particular skills exhibited during interaction. In addition, this valuable provision of information is used as a meta cognitive tool for tutors and moderators for monitoring and evaluating the discussion process more conveniently. This contribution presents our conceptual model for interaction management as well as key design guidelines and evaluation results. Implications of this study are remarked and further research directions are proposed.     

Symbolic modular deadlock analysis

Methods in object-oriented concurrent libraries often encapsulate internal synchronization details. As a result of information hiding, clients calling the library methods may cause thread safety violations by invoking methods in an unsafe manner. This is frequently a cause of deadlocks. Given a concurrent library, we present a technique for inferring interface contracts that specify permissible concurrent method calls and patterns of aliasing among method arguments. In this work, we focus on deriving contracts that guarantee deadlock-free execution for the methods in the library. The contracts also help client developers by documenting required assumptions about the library methods. Alternatively, the contracts can be statically enforced in the client code to detect potential deadlocks in the client. Our technique combines static analysis with a symbolic encoding scheme for tracking lock dependencies, allowing us to synthesize contracts using a SMT solver. Additionally, we investigate extensions of our technique to reason about deadlocks in libraries that employ signaling primitives such as wait-notify for cooperative synchronization. Our prototype tool analyzes over a million lines of code for some widely-used Java libraries within an hour, thus demonstrating its scalability and efficiency. Furthermore, the contracts inferred by our approach have been able to pinpoint real deadlocks in clients, i.e. deadlocks that have been a part of bug-reports filed by users and developers of client code.     

Design and fabrication of a freeform microlens array for uniform beam shaping

Freeform optics has become a practical solution to solving number of problems in modern optical design. In this paper, we proposed a fabrication method using the combination of ultraprecision diamond machining and microinjection molding to achieve high volume and low cost freeform microlens manufacturing. The freeform microlens array discussed in this research is capable of redistributing a collimated light into a pre determined, in this case, a uniform pattern. The optical design, slow tool servo diamond machining, microinjection molding process and optical measurement were discussed. The simple optical design provided a platform for freeform microlens calculation. Slow tool servo diamond broaching was selected to fabricate the mold insert. After the mold insert was fabricated, microinjection molding machine was utilized to replicate the optical geometry into plastic substrates. The freeform microlens array that was fabricated in this research could achieve light re-distribution at the target with approximately 80% uniformity. The research conducted in this paper can be readily implemented in optical industry.     

Parallel force measurement with a polymeric microbeam array using an optical microscope and micromanipulator

An image analysis method and its validation are presented for tracking the displacements of parallel mechanical force sensors. Force is measured using a combination of beam theory, optical microscopy, and image analysis. The primary instrument is a calibrated polymeric microbeam array mounted on a micromanipulator with the intended purpose of measuring traction forces on cell cultures or cell arrays. One application is the testing of hypotheses involving cellular mechanotransduction mechanisms. An Otsu-based image analysis code calculates displacement and force on cellular or other soft structures by using edge detection and image subtraction on digitally captured optical microscopy images. Forces as small as 250+/-50 nN and as great as 25+/-2.5 microN may be applied and measured upon as few as one or as many as hundreds of structures in parallel. A validation of the method is provided by comparing results from a rigid glass surface and a compliant polymeric surface.     

Biomarkers in pediatrics: children as biomarker orphans

Biomarkers have enormous potential to improve patient care by establishing tests of diagnosis, prognosis, and treatment effects. Successfully translating a biomarker from discovery to clinical application demands high-quality discovery research and high-quality clinical studies for biomarker validation; however, there are additional challenges that face biomarker research in pediatrics. There are also additional characteristics of pediatric medicine that make biomarker research especially needed. This review focuses on the fundamentals of biomarkers, the additional considerations needed for applying biomarker research to children, and recommendations for advancing pediatric biomarker research.     

Processing and characterisation of precision microparts from nickel-based materials

The objective of this research was to study the influence of electroplating parameters on electrodeposit characteristics for the production of nickel (Ni) and nickel–iron (Ni–Fe) microparts by photoelectroforming. The research focused on the most relevant parameter for industry, which is the current density, because it determines the process time and the consumed energy. The results of the Ni and Ni–Fe characterisations can be divided into two aspects closely linked with each other: the morphology and the hardness.     

On improving the efficiency of tensor voting

This paper proposes two alternative formulations to reduce the high computational complexity of tensor voting, a robust perceptual grouping technique used to extract salient information from noisy data. The first scheme consists of numerical approximations of the votes, which have been derived from an in-depth analysis of the plate and ball voting processes. The second scheme simplifies the formulation while keeping the same perceptual meaning of the original tensor voting: The stick tensor voting and the stick component of the plate tensor voting must reinforce surfaceness, the plate components of both the plate and ball tensor voting must boost curveness, whereas junctionness must be strengthened by the ball component of the ball tensor voting. Two new parameters have been proposed for the second formulation in order to control the potentially conflictive influence of the stick component of the plate vote and the ball component of the ball vote. Results show that the proposed formulations can be used in applications where efficiency is an issue since they have a complexity of order O(1). Moreover, the second proposed formulation has been shown to be more appropriate than the original tensor voting for estimating saliencies by appropriately setting the two new parameters.     

Multi‐agent system for knowledge‐based event recognition and composition

This work presents a multi‐agent system for knowledge‐based high‐level event composition, which interprets activities, behaviour and situations semantically in a scenario with multi‐sensory monitoring. A perception agent (plurisensory agent and visual agent)‐based structure is presented. The agents process the sensor information and identify (agent decision system) significant changes in the monitored signals, which they send as simple events to the composition agent that searches for and identifies pre‐defined patterns as higher‐level semantic composed events. The structure has a methodology and a set of tools that facilitate its development and application to different fields without having to start from scratch. This creates an environment to develop knowledge‐based systems generally for event composition. The application task of our work is surveillance, and event composition/inference examples are shown which characterize an alarming situation in the scene and resolve identification and tracking problems of people in the scenario being monitored.